Datacenter workload modeling has become a necessity in recent years due to the emergence of large-scale applications and cloud data-stores, whose implementation remains largely unknown. Detailed knowledge of target workloads is critical in order to correctly provision performance, power and cost-optimized systems. In this work we aggregate previous work on datacenter workload modeling and perform a qualitative comparison based on the representativeness, accuracy and completeness of these designs. We categorize modeling techniques in two main approaches, in-breadth and in-depth, based on the way they address the modeling of the workload. The former models the behavior of a workload in specific system parts, while the latter traces a user request throughout its execution. Furthermore, we propose the early concept of a new design, which bridges the gap between these two approaches by combining some features from each one. Some first performance results based on this design appear promi...